IN54A-01
Multi-Resolution Motion-Compensated Analysis of Sea Surface Temperature
The sea surface temperature (SST) fields in various scientific and operational applications are presented at very different spatial and temporal scales. For example, a global SST mean over a long time period is often examined in climate studies, while an SST snapshot of sub-kilometer resolution may be desired in some biological studies. Also, when used as a boundary condition of atmospheric dynamics (weather forecast) models, the SST field is often resolved only down to a spatial scale that matches the numerical resolution in the particular model in order to avoid spurious dynamical behaviors. Resolution and span in space and time of SST analysis are thus application dependent. Our project focuses on analysis of the satellite-based measurements to address these variety of needs for SST. Satellite-based SST data are irregularly-sampled by different sensor types. Geostationary satellites have fine temporal resolutions but cover only limited geographical regions, while orbiting satellites can have global coverages by compromising temporal sampling. The microwave (MW) sensors have typically coarser 25-km resolution than the infra-red (IR) sensors which can resolve down to a 1-km scale. However, the IR-based measurements are prone to data voids due to cloud contamination, which does not affect MW sensors nearly as much. In this talk, we present a method to merge these satellite SST measurements with drastically different spatial resolution and coverage. We employ a wavelet-based, multi-resolution analysis technique to ensure consistency of our analysis with the self-similar (power-law) characteristics observed empirically over a wide range of wavenumber spectrum. Also, to deal with the data voids which can be both persistent in time and recurrent over particular geographical regions, we employ a motion-compensated analysis technique to avoid temporal smearing of small-scale coherent patterns. We will implement subsetting and near real-time capability to deliver the SST products "on demand" at various spatial coverages and resolutions down to 1 km.
IN54A-02
Understanding the Differences Between AIRS, MODIS and ASTER Land Surface Emissivity Products
One of the key Earth Science Data Records identified by NASA is Land Surface Temperature and Emissivity (LST&E). LST&E data are key parameters in global climate change studies that involve climate modeling, ice dynamic analyses, surface-atmosphere interactions and land use, land cover change. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on NASA's Aqua satellite, are strongly dependent on using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions where the variation in emissivity is large, both spatially and spectrally. LST&E standard products are available from spaceborne sensors such as AIRS, MODIS and ASTER at varying spatial, spectral, and temporal resolutions. Although these emissivity products represent the same measure, there are frequently discrepancies between the products associated with different scientific approaches used that need to be better understood. For example, ASTER provides LST&E data with the highest spatial resolution (90 m), compared with AIRS (50 km) and MODIS (1 and 5 km). AIRS has the highest spectral sampling and both AIRS and MODIS acquire data at much higher temporal frequencies (every 2-3 days) compared with ASTER (16 days). In this paper we present validation and intercomparisons of AIRS, MODIS and ASTER gridded emissivity products over North America. MODIS and ASTER data will be upsampled to the AIRS spatial resolution, and then compared to laboratory measured emissivities of in-situ rock/sand samples collected at ten validation sites in the Western USA during 2008. The directional hemispherical reflectance of the in-situ samples are measured in the laboratory using a Nicolet Fourier Transform Interferometer (FTIR), converted to emissivity using Kirchoff's law, and convolving to the appropriate sensor's spectral response functions. We present here some of the first quantitative results on the differences between emissivity products from different sensors as a result of differences in spatial, spectral and temporal resolutions, and furthermore, comparisons with laboratory results will give a measure of the accuracy of the emissivity products - a critical aspect for the broad scientific community in deriving accurate land surface temperatures.
IN54A-03
An Approach for Developing Earth Science Data Records of Global Forest Cover Change
There is long-standing recognition of the need for global forest change detection at Landsat-class resolutions. Previously this was not feasible, because of the absence of well registered multi-temporal data sets, variations in sensors, the need for intensive human input during post-processing, variations in spectral responses of forests, the efforts needed to create validation data sets and the computational and storage demands in carrying out the analysis. We will demonstrate in this presentation that these problems have now been largely overcome by the availability of the Global Landsat Survey (GLS) data sets, our ability to create atmospherically corrected reflectance products, much improved classifiers, collection of automated dense training sets, the availability of ultra-fine resolution datasets and much lower computational costs. We will present an approach for producing the following Earth Science Data Records (ESDR) at fine and moderate spatial resolutions: - Global fine resolution (< 100 m) surface reflectance ESDR for four epochs centered around 1990, 2000, and 2005; - Fine resolution (< 100 m) forest cover change (FCC) ESDR between the three epochs; - Fragmentation products derived from the fine resolution FCC products; - Global 250-m vegetation continuous field (VCF) based FCC ESDR from 2000 to 2005; - FCC ESDR products aggregated from the fine resolution and the 250 m FCC products to 250 m, 500 m, 1 km, and 0.05 degree grids for use by carbon, biogeochemical and hydrological modelers.
IN54A-04
Vegetation Phenology and Vegetation Index Products from Multiple Long Term Satellite Data Records
Phenology is the expression of the seasonal cycle of all biotic processes. It is the pulse of our planet, and is
an essential and critical component of environmental science influencing biodiversity, species interactions,
their ecological functioning, and their effects on fluxes of water, energy, and biogeochemical elements at
various scales. Changes in phenology depict an integrated response to environmental change and provide
valuable information for global change research, land degradation studies, integrated pest and invasive
species management, drought monitoring, wildfire risk assessment, and agricultural production.
In this NASA Making Earth System data records for Use in Research Environments (NASA-MEaSUREs)
project our multi-institution team of investigators plans to generate a seamless and consistent sensor
independent Earth System Data Record and Climate Data Record (ESDR/CDR) quality measures of
landscape phenology and vegetation index (VI), by fusing measurements from different satellite missions and
sensors. We plan to use the AVHRR, MODIS and VIIRS daily surface reflectance products and design
sensor independent algorithms that can be applied to these multi-sensor data sets. Our project aims at
generating, documenting, and delivering 30+ years of consistent and well characterized ESDR/CDR quality
daily measurements of land surface VI and annual phenology parameters at a climate modeling grid
resolution (CMG, 0.05 deg).
In collaboration with the newly established USA national phenology network (USA-NPN), we plan to correlate
these remote sensing based measurements of phenology and VI with ground observations. We aim at
evaluating the consistency and accuracy of these products by comparing them with in situ growing season
phenology observations over different biomes, latitudinal and elevational gradients.
We plan to distribute these products through the USGS EROS center and support them via a web based
interactive visualization system. We will enlist key science and modeling community users, as well as the
USA-NPN, in the process of evaluating the merits of these ESDR/CDR products. A user working group
(UWG) will advise this effort and link it with the wider national and international user and scientific
communities.
http://phenology.arizona.edu
IN54A-05
Making Intercalibrated, Multi-Instrument Microwave Earth Science Data Records
Microwave radiometers have been operating since 1987 in polar orbits around the earth on a succession of
DMSP satellites. When consistently processed, data from these instruments result in a long-term high-quality
Earth science data record (ESDR) of ocean surface winds, atmospheric water vapor, cloud liquid water, rain
rates, and sea surface temperatures. This suite of ocean data products has been publicly available since
1996; funded successively by the NASA Pathfinder, ESIP, REASoN and now MEaSUREs programs. The
DISCOVER (Distributed Information Services for Climate and Ocean Products and Visualizations for Earth
Research) project involves the intercalibration, consistent processing, validation, distribution and support of
these ocean data. This talk will present the algorithm history, outline the many steps required to make the
DISCOVER products, describe how these data are being used within the community, and show how we
support our data users. In addition, we will present the challenges faced when adding new instruments to
the data record. The value of any particular ESDR can be determined by its use as this is a means of
understanding the confidence the community has in the algorithm and the products. We will provide
information on the distribution and incorporation of the DISCOVER ocean data into other value-added
products and summarize the ways the DISCOVER data have contributed to improved understanding of the
Earth's water and energy budget, air-sea interaction, and decadal scale climate changes.
http://www.discover-earth.org/
IN54A-06
Changes in Aerosols and Cloud Reflectivity (1979-2008) From 30 Years of Radiance Data using Multiple Satellites: N7-TOMS, EP-TOMS, SBUV-2 Series, SeaWiFS, and OMI
The amount of solar radiation reflected back to space or reaching the Earth's surface is primarily governed by the amount of cloud cover, and, to a much lesser extent, by aerosols and various absorbing gases (e.g., O3, NO2, H2O) in their relative bands of absorption. A useful measure of the effect of cloud plus aerosol cover is given by the amount that the UV (331nm to 400 nm) Lambert Equivalent Reflectivity (LER) of a scene exceeds the surface reflectivity for snow/ice-free scenes. A 30-year reflectivity time series is presented by combining data from several satellites: N7 (Nimbus-7 TOMS; 331 nm) from 1979 to 1992, SBUV-2 series (Solar Backscatter UltraViolet-NOAA N9, N11, N16, N17, N18; 331 nm) 1985 to 2007, EP (Earth-Probe TOMS; 331 nm) 1997 to 2006, SW (SeaWiFS; 412 nm) 1998 to 2007, and OMI (Ozone Measuring Instrument; 331 nm) 2004 - 2007. Only N7 and SW have a sufficiently long data record and are adequately calibrated for long-term reflectivity trend estimation by themselves. Values derived from these instruments and the SBUV-2 series obtained during the overlapping years are compared. Key issues in determining long- term reflectivity changes that have occurred during the N7 and SW operating periods are discussed, as are the problems in re-calibrating all of the TOMS and SBUV satellite data. The preliminary combined 30-year reflectivity data set shows a small global increase in radiation reflected back to space suggestive of global dimming at the surface.
IN54A-07
GOZCARDS: Global Ozone Chemistry and Related Trace gas Data Records for the Stratosphere
We describe plans and early results for this multi-year MEaSUREs project, aiming to provide a commonly-
formatted Earth system data record (ESDR) for stratospheric
composition, of high relevance to the issue of ozone decline and recovery. The data records will be drawn
primarily from satellite-derived global stratospheric composition measurements from 1979 to the present,
along with on-going measurements, as well as temperatures from GMAO GEOS-5 meteorological analyses.
These data records will provide time series for stratospheric ozone (O3), hydrogen chloride (HCl), chlorine
monoxide (ClO), nitric acid (HNO3), water vapor (H2O), nitrous oxide (N2O), nitrogen dioxide (NO2), nitrogen
oxide (NO), methane (CH4), and hydrogen fluoride (HF). Additional "derived data records", using a
constrained photochemical model, will be provided for active chlorine (ClOx) and odd nitrogen (NOx). The
GMAO data will also lead to a consistent set of stratospheric ozone column abundances, based on
tropopause height estimates; in addition, we will produce derived quantities relating to ozone loss in the polar
regions. These quantities will include the volume and area of air with temperatures below PSC formation
thresholds.
The satellite-based profiles come from SAGE I (providing O3 and NO2), SAGE II, SAGE III, POAM II, and
POAM III (for O3, H2O, and NO2), HALOE (for O3, HCl, H2O, NO, NO2, CH4, and HF), and UARS MLS (for
O3, ClO, and H2O). The "operational" records (going forward in time) will depend on Aura MLS products (for
O3, HCl, ClO, HNO3, H2O, N2O) and SciSat-1 ACE-FTS profiles (for O3, HCl, ClO, HNO3, H2O, N2O, NO,
NO2, CH4 and HF).
These data will be provided as averages versus latitude on a common vertical grid, with time resolution of
one month as a standard, and one day when possible. Data records binned in equivalent latitude and
potential temperature will also be
provided. We will strive to provide both the original records and merged data records, with user options for
the offsets to be applied. Web-based data access to commonly-formatted files and various related plots will
be provided.
IN54A-08
The 29-year Global Precipitation Climatology Project (GPCP) Analysis: Results, Status and Future
The Global Precipitation Climatology Project (GPCP) is one of a number of long-term, satellite-based, global analyses routinely produced under the auspices of the World Climate Research Program (WCRP) and its Global Energy and Watercycle EXperiment (GEWEX) program. The research quality analyses are produced a few months after real-time through the efforts of scientists at various national agencies and universities in the U.S., Europe and Asia. The primary product is a monthly analysis of surface precipitation that is globally complete and spans the period 1979-present. There are also pentad analyses for the same period and a daily analysis for the 1997-present period. Although generated with somewhat different data sets and analysis schemes, the pentad and daily data sets are forced to agree with the primary monthly analysis on a grid box by grid box basis. The primary input data sets are from low-orbit passive microwave observations, geostationary infrared observations and surface raingauge information. Examples of research with the data sets are discussed, focusing on precipitation variations and possible long-term changes in the 29-year (1979-2007) monthly dataset. Techniques are used to discriminate among the variations due to ENSO, volcanic events and possible long-term changes for rainfall over both land and ocean. Although the global change of precipitation in the data set is near zero, a small upward linear change over the Tropics, primarily over the ocean (0.06 mm/day/10yr), is described along with other less significant 'trend' features at other latitudes. The validity of inter-annual precipitation variations in the data set at high latitudes is explored using a new comparison with gauge information over Finland. The final merged satellite-gauge monthly GPCP product compares well with the higher density gauge data set, as expected. When the satellite-only intermediate product is used in the comparison the correlations fall to ~ 0.65 from ~ 0.95, clearly indicating the value of even a small amount of gauge information at this latitude to restrain the bias. The lower, but still significant, correlation of the satellite product is probably representative of results over high latitude ocean and high latitude land areas with no gauges. Validation of the daily GPCP analysis with the same dense gauge network is also presented. A new, version 3 of GPCP is being planned to incorporate new satellite information (e.g., TRMM) and provide higher spatial and temporal resolution for at least part of the data record. The goals and plans for that GPCP re-processing will be outlined.
IN54A-09
Development of a New Cross-Calibrated Multiple Satellite Ocean Surface Wind Data Set
A new set of cross-calibrated, multi-satellite ocean surface wind data is available under NASA's MEaSURE
program. The principal data set covers the global ocean for the period beginning in 1987 with six-hour and
25-km resolution, and is produced by combining all ocean surface wind speed observations from SSM/I,
AMSR-E, and TMI, and all ocean surface wind vector observations from QuikSCAT and SeaWinds. An
enhanced variational analysis method (VAM) performs quality control and combines these data with available
conventional ship and buoy data and ECMWF analyses. The VAM analyses fit the data used very closely
and contain small-scale structures not present in operational analyses. Comparisons with withheld WindSat
observations are also shown to be very good. These data sets should be extremely useful to atmospheric
and oceanic research, and to air-sea interaction studies. Some early results and the methodology used to
create this ESDR will be presented.
http://podaac.jpl.nasa.gov/DATA_CATALOG/ccmpinfo.html
IN54A-10
Moving Climate Data Records from Research to Operations
The Nation and broader scientific community have a pressing need for the routine and systematic production
of Climate Data Records (CDRs), a position strongly supported through recent reports from the U.S. Climate
Change Science Program (CCSP), the Global Climate Observing System (GCOS) and the Intergovernmental
Panel on Climate Change (IPCC) Fourth Assessment Report. The National
Academy's Earth Science 'Decadal
Survey' (2007) recommended interagency coordination in the developing these
products. In response, representatives from NOAA's National Climatic Data Center,
NASA Headquarters and the U.S. Geological Survey have been developing a conceptual framework for
systematically moving mature satellite algorithms from the research domain into sustained and coherent
operational production and, as appropriate, into Climate Information Records (CIRs). Notionally entitled
'The Evolution of a CDR', the strategy includes continuing
opportunities to develop new research algorithms, the systematic evolution, generalization and maintenance
of mature research algorithms, the routine generation, validation and stewardship of CDRs and CIRs, and
support of climate studies based on CDRs and CIRs. It also defines product maturity levels, a critical notion
for identifying the appropriate agency for current support and the further steps required for the research-to-
operations transition and CDR release. NOAA's National Climatic Data Center
(NCDC) initiated the Scientific Data Stewardship (SDS) Project to lead the NOAA's
CDR activities and to coordinate with the partner agencies. The SDS Project expects to execute its
responsibilities in partnership with the larger scientific community through annual NOAA Announcements of
Opportunity -- open to academic, commercial, non-profit and government proposers -- as well as through
community reviews and working groups. This presentation will describe the Evolution of a CDR/CIR concept,
NOAA's SDS approach, initial goals and objectives, and a vision for the future.
http://www.ncdc.noaa.gov/sds/index.html